Malicious vehicle detection scheme based on UAV and vehicle cooperative authentication in vehicular networks

IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Computer Networks Pub Date : 2025-02-01 Epub Date: 2025-01-10 DOI:10.1016/j.comnet.2025.111037
Wenming Wang , Zhiquan Liu , Lingyan Xue , Haiping Huang , Nageswara Rao Lavuri
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Abstract

The advancement of the vehicular networks has significantly enhanced the capabilities of intelligent transportation systems. However, the transmission of malicious information (e.g., false emergency alerts or traffic congestion updates) by comprised vehicles poses a serious threat to emergency response operations, particularly in mountainous regions where signal quality is poor. Recent developments in integrating Unmanned Aerial Vehicles (UAVs) with vehicular networks have introduced new opportunities for enhancing network security, enhancing network security in these challenging environments. In response to these challenges, this paper proposes a UAV and vehicle cooperative authentication scheme for detecting malicious vehicles within vehicular networks. The proposed approach reduces overhead through cooperative authentication between vehicles, while UAVs monitor vehicle behavior in real-time. Additionally, Trusted Centers of Authority (TCAs) are employed to oversee UAV activities, ensuring the integrity of the system. The TCA dynamically allocates suitable UAVs for tasks based on real-time availability, optimizing resource utilization. Furthermore, the proposed scheme introduces a hierarchical TCAs structure, partitioning it into root_TCA and sub_TCA, which mitigates the risk of single points of failure and improves resource efficiency. Comparative analysis demonstrates that the proposed scheme offers superior performance in terms of computational and communication overhead compared to existing methods.
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基于无人机和车辆协同认证的车联网恶意车辆检测方案
车联网的发展极大地增强了智能交通系统的能力。但是,组队车辆传输恶意信息(例如虚假的紧急警报或交通拥堵情况更新)对应急行动构成严重威胁,特别是在信号质量差的山区。无人机(uav)与车载网络集成的最新发展为增强网络安全带来了新的机遇,增强了这些具有挑战性环境中的网络安全。针对这些挑战,本文提出了一种用于检测车载网络中恶意车辆的无人机与车辆协同认证方案。该方法通过车辆之间的协作认证减少了开销,同时无人机实时监控车辆的行为。此外,可信权威中心(tca)被用来监督无人机活动,确保系统的完整性。该算法基于实时可用性动态分配适合任务的无人机,优化资源利用率。此外,该方案引入了分层tca结构,将其划分为root_TCA和sub_TCA,降低了单点故障的风险,提高了资源效率。对比分析表明,与现有方法相比,该方案在计算量和通信开销方面具有更好的性能。
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来源期刊
Computer Networks
Computer Networks 工程技术-电信学
CiteScore
10.80
自引率
3.60%
发文量
434
审稿时长
8.6 months
期刊介绍: Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.
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